Evidence map›Paper›PMID 31601233›Full record

ReviewGlobalization and health2019

Getting the most from after action reviews to improve global health security.

Michael A Stoto, Christopher Nelson, Rachael Piltch-Loeb, Landry Ndriko Mayigane, Frederik Copper, Stella Chungong

Abstract readReview
In one paragraph

Review in Globalization and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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  17. A methodological approach to intra-action reviews - application and adaptation of existing global guidance during the COVID-19 pandemic response in Ireland, 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023
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  19. Applying after action review to examine residential treatment programs' responses to COVID-19.The International journal of health planning and management · 2022
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  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Michael A StotoGeorgetown University Center for Global Health Science & Security, 3700 Reservoir Road, NW, Washington, DC, 20057-1107, USA. stotom@georgetown.edu.ORCID 0000-0001-8293-471X
Christopher NelsonRAND Corporation and RAND Pardee Graduate School, Santa Monica, CA, USA.
Rachael Piltch-LoebHarvard T.H. Chan School of Public Health, Boston, MA, USA.
Landry Ndriko MayiganeCore Capacity Assessment, Monitoring and Evaluation (CME) Unit Country Health Emergency Preparedness and IHR Department, WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.
Frederik CopperCore Capacity Assessment, Monitoring and Evaluation (CME) Unit Country Health Emergency Preparedness and IHR Department, WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.
Stella ChungongCore Capacity Assessment, Monitoring and Evaluation (CME) Unit Country Health Emergency Preparedness and IHR Department, WHO Health Emergencies Programme, World Health Organization, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundAfter Action Reviews (AARs) provide a means to observe how well preparedness systems perform in real world conditions and can help to identify - and address - gaps in national and global public health emergency preparedness (PHEP) systems. WHO has recently published guidance for voluntary AARs. This analysis builds on this guidance by reviewing evidence on the effectiveness of AARs as tools for system improvement and by summarizing some key lessons about ensuring that AARs result in meaningful learning from experience.

resultsEmpirical evidence from a variety of fields suggests that AARs hold considerable promise as tools of system improvement for PHEP. Our review of the literature and practical experience demonstrates that AARs are most likely to result in meaningful learning if they focus on incidents that are selected for their learning value, involve an appropriately broad range of perspectives, are conducted with appropriate time for reflection, employ systems frameworks and rigorous tools such as facilitated lookbacks and root cause analysis, and strike a balance between attention to incident specifics vs. generalizable capacities and capabilities.

conclusionsEmploying these practices requires a PHEP system that facilitates the preparation of insightful AARs, and more generally rewards learning. The barriers to AARs fall into two categories: concerns about the cultural sensitivity and context, liability, the political response, and national security; and constraints on staff time and the lack of experience and the requisite analytical skills. Ensuring that AARs fulfill their promise as tools of system improvement will require ongoing investment and a change in mindset. The first step should be to clarify that the goal of AARs is organizational learning, not placing blame or punishing poor performance. Based on experience in other fields, the buy-in of agency and political leadership is critical in this regard. National public health systems also need support in the form of toolkits, guides, and training, as well as research on AAR methods. An AAR registry could support organizational improvement through careful post-event analysis of systems' own events, facilitate identification and sharing of best practices across jurisdictions, and enable cross-case analyses.

Indexed as

Global HealthPublic HealthDisaster PlanningDisease OutbreaksHumansAfter action reports (AARs)After action reviews (AARs)Critical incident reviewsPublic health emergenciesPublic health preparednessSystems improvement

Identifiers

PMID31601233
PMCPMC6785939

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.